1. Field of the Invention
The present invention relates to a machine learning apparatus and a machine learning method for learning a condition associated with the predicted life of a motor, a life prediction apparatus and a motor system including the machine learning apparatus.
2. Description of the Related Art
In a field using a motor, in order to prevent reduction in operational efficiency and occurrence of a serious accident, the life of the motor is predicted, and based on the prediction result, replacement or maintenance such as repairing and mending of the motor or a component thereof is performed before the motor becomes inoperable due to the end of the life of the motor. Conventionally, the designer and user of a motor predicts the life of the motor by performing an experiment or the like. In some cases, the designer and user predict the life of the motor based on their rule of thumb.
As disclosed in, for example, Japanese Laid-open Patent Publication No. S60-144127, there is known a method for predicting the life of a motor by seeking a failure model that represents a relationship between winding temperature and winding failure rate of the motor.
Further, as disclosed in, for example, Japanese Laid-open Patent Publication No. 2006-98349, there is known a method for predicting the insulation life of an insulator provided to a rotor coil in a high voltage rotary machine.
Further, as disclosed in, for example in Japanese Laid-open Patent Publication No. 2003-130048, there is known a method for predicting the life of a rolling bearing, which is a component of a motor.
However, the life varies depending on the use environment of the motor. Thus, life prediction for the motor by an experiment sometimes lacks accuracy. Further, it takes much time and labor to reproduce an experiment depending on individual use environment to seek accuracy, and that is cumbersome. In addition, that is inefficient due to the dependence on a personal rule of thumb, and also there is a big personal difference.